• The Korean Journal of Quaternary Research
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• v.19 no.2
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• pp.74-79
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• 2005

Recently, several attempts have been made to provide reasonable information on unusual severe weather phenomena such as tolerant heavy rains and very wild typhoons. Quantitative precipitation forecasts and probabilistic quantitative precipitation forecasts (QPFs and PQPFs, respectively) might be one of the most promising methodologies for early warning on the flesh floods because those diagnostic precipitation models require less computational resources than fine-mesh full-dynamics non-hydrostatic mesoscale model. The diagnostic rainfall model used in this study is the named QPM(Quantitative Precipitation Model), which calculates the rainfall by considering the effect of small-scale topography which is not treated in the mesoscale model. We examine the capability of probabilistic diagnostic rainfall model in terms of how well represented the observed several rainfall events and what is the most optimistic resolution of the mesoscale model in which diagnostic rainfall model is nested. Also, we examine the integration time to provide reasonable fine-mesh rainfall information. When we apply this QPM directly to 27 km mesh meso-scale model (called as M27-Q3), it takes about 15 min. while it takes about 87 min. to get the same resolution precipitation information with full dynamic downscaling method (called M27-9-3). The quality of precipitation forecast by M27-Q3 is quite comparable with the results of M27-9-3 with reasonable threshold value for precipitation. Based on a series of examination we may conclude that the proosed QPM has a capability to provide fine-mesh rainfall information in terms of time and accuracy compared to full dynamical fine-mesh meso-scale model.

• International Journal of Oral Biology
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• v.43 no.2
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• pp.101-111
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• 2018

Understanding the classification of malocclusion is a crucial issue in Orthodontics. It can also help us to diagnose, treat, and understand malocclusion to establish a standard for definite class of patients. Principal component analysis (PCA) and k-means algorithms have been emerging as data analytic methods for cephalometric measurements, due to their intuitive concepts and application potentials. This study analyzed the macro- and meso-scale classification structure and feature basis vectors of 1020 (415 male, 605 female; mean age, 25 years) orthodontic patients using statistical preprocessing, PCA, random matrix theory (RMT) and k-means algorithms. RMT results show that 7 principal components (PCs) are significant standard in the extraction of features. Using k-means algorithms, 3 and 6 clusters were identified and the axes of PC1~3 were determined to be significant for patient classification. Macro-scale classification denotes skeletal Class I, II, III and PC1 means anteroposterior discrepancy of the maxilla and mandible and mandibular position. PC2 and PC3 means vertical pattern and maxillary position respectively; they played significant roles in the meso-scale classification. In conclusion, the typical patient profile (TPP) of each class showed that the data-based classification corresponds with the clinical classification of orthodontic patients. This data-based study can provide insight into the development of new diagnostic classifications.

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2367-2375
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• 2022

In this work, we propose a new mechanistic model for the treatment of helium behaviour at the grain boundaries in oxide nuclear fuel. The model provides a rate-theory description of helium inter-granular behaviour, considering diffusion towards grain edges, trapping in lenticular bubbles, and thermal resolution. It is paired with a rate-theory description of helium intra-granular behaviour that includes diffusion towards grain boundaries, trapping in spherical bubbles, and thermal re-solution. The proposed model has been implemented in the meso-scale software designed for coupling with fuel performance codes SCIANTIX. It is validated against thermal desorption experiments performed on doped UO₂ samples annealed at different temperatures. The overall agreement of the new model with the experimental data is improved, both in terms of integral helium release and of the helium release rate. By considering the contribution of helium at the grain boundaries in the new model, it is possible to represent the kinetics of helium release rate at high temperature. Given the uncertainties involved in the initial conditions for the inter-granular part of the model and the uncertainties associated to some model parameters for which limited lower-length scale information is available, such as the helium diffusivity at the grain boundaries, the results are complemented by a dedicated uncertainty analysis. This assessment demonstrates that the initial conditions, chosen in a reasonable range, have limited impact on the results, and confirms that it is possible to achieve satisfying results using sound values for the uncertain physical parameters.

• Journal of Korea Water Resources Association
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• v.44 no.2
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• pp.97-107
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• 2011

For the purpose of enhancing usability of NWP (Numerical Weather Prediction), the quantitative precipitation prediction scheme was suggested. In this research, precipitation by leading time was predicted using 3-hour rainfall accumulation by meso-scale numerical weather model and AWS (Automatic Weather Station), precipitation water and relative humidity observed by atmospheric sounding station, probability of rainfall occurrence by leading time in June and July, 2001 and August, 2002. Considering the nonlinear process of ranfall producing mechanism, the ANN (Artificial Neural Network) that is useful in nonlinear fitting between rainfall and the other atmospheric variables. The feedforward multi-layer perceptron was used for neural network structure, and the nonlinear bipolaractivation function was used for neural network training for converting negative rainfall into no rain value. The ANN simulated rainfall was validated by leading time using Nash-Sutcliffe Coefficient of Efficiency (COE) and Coefficient of Correlation (CORR). As a result, the 3 hour rainfall accumulation basis shows that the COE of the areal mean of the Korean peninsula was improved from -0.04 to 0.31 for the 12 hr leading time, -0.04 to 0.38 for the 24 hr leading time, -0.03 to 0.33 for the 36 hr leading time, and -0.05 to 0.27 for the 48 hr leading time.

• Journal of the Korean Geographical Society
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• v.13
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• pp.13-19
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• 1976

본 고에서는 기후학연구의 동향을 대략 살펴보고자 한다. 우리나라 기후학연구의 시작은 해방과 한국동란의 긴 격동기를 거쳐 1960년대에 들어와서라고 할 수 있고, 본격적인 연구는 1970년대에 들어서면서라고 볼 수 있다. 연구분야에 있어서는 기후분류를 주로했던 초기단계에서 기후요소나 변동을 다루게 되었고 최근에는 기후지형, 수분수지, 기단기후, 체감기후등의 방향으로 관심이 높아졌다. 그러나 meso scale이나 micro scale의 연구가 개척되지 않고 macro scale의 기후연구에 머물러 있는 감이 있다. 60년대 후반에서 70년대 초반에 걸친 우리나라의 산업근대화나 인구의 증가, 급속한 도시화에 따라 중기후나 소기후 연구의 필요성이 높아졌고 특히 일약팽창하는 도시에 있어서의 기후환경의 연구는 현대생활에 불가피의 과제이다. 이 방면에 약간의 연구가 시작되기는 하였지만 아직도 많은 연구문제가 방치되어있다. 중.소기후의 연구에는 현재보다 훨씬 많은 관측망의 설치가 선행되어야 할 것이며 도시기후의 관측에는 관측계기나 관측에 따르는 재정적인 문제가 달려있다. 이와같은 분야의 연구는 연구 team의 문제도 있어 개인연구로서는 도저히 감당하기 어려운 분야이다. 따라서 연구기관이나 국가의 지원하에 도시기후의 공동연구가 추진되어야 할 것이다.

• Journal of Environmental Impact Assessment
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• v.11 no.2
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• pp.109-116
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• 2002

The diagnostic and prognostic methods for generating 3 dimensional wind field were comparatively analyzed and 4 dimensional data assimilation (FDDA) technique by incorporating Automatic Weather System (AWS) into the prognostic methods was discussed for the urban scale air quality model. The A WS covered the urban scale grid distance of 10.6 km and 4.3 km in South Korea and Kyong-in region, respectively. This is representing that AWS for FDDA could be fairly well accommodated in prognostic model with the meso${\gamma}$~ microa scale (~5 km), indicating that the 3 dimensional wind field by FDDA technique could be a useful interpretative tool in urban area for the atmospheric environmental impact assessment.

• Transactions of Materials Processing
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• v.15 no.3 s.84
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• pp.247-254
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• 2006

Rather than traditional manufacturing processes, miniature manufacturing processes usually require sophisticated equipments and characteristics of the processes of high cost and of low productivity. Contrarily, miniature stamping process can be realized in a low cost high productivity with relatively inexpensive equipments. In the meso scale, mechanical properties, especially work hardening characteristics, are discovered to be statically scattered and size dependent by intensive experimental and numerical investigations, which make the stamping process hard to apply to the miniature manufacturing. In this study, dual purpose experimental device that can be used for both miniature scale tensile test and miniature scale stamping by simple change of attachment has been developed. For the tensile test, the elongation has been measured with a combined use of a CCD camera and a linear encoder in order to account for the possibility of slippage between specimen and the grip and to ensure the accuracy of the measurement, while load has been measured with a load cell. To satisfy the required material properties for stamping, optimal annealing condition has been found by examining the microstructure of annealed specimen.

• Journal of the Korea Concrete Institute
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• v.18 no.2 s.92
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• pp.189-198
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• 2006

The composition of most engineering materials is heterogeneous at some degree. It is simply a question of scale at which the level of heterogeneity becomes apparent. In the case of cementitious granular materials such as concrete the heterogeneity appears at the mesoscale where it is comprised of aggregate particles, a hardened cement paste and voids. Since it is difficult to consider each separate particle in the topological description explicitly, numerical models of the meso-structure are normally confined to two-phase matrix particle composites in which only the larger inclusions are accounted for. 2-D and 3-D concrete blocks(Representative Volume Element, RVE) are used to simulating heterogeneous concrete meso-structures in the form of aggregates in the hardened mortar with nearly zero-thickness linear or planar interfaces. The numerical sensitivity of these meso-structures are Investigated with respect to the different morphologies of heterogeneity and the different level of coupling constant among fracture mode I, II and III. In addition, a numerically homogenized concrete block in 3-D using Hashin-Shtrikman variational bounds provides an evidence of the effective cracking paths which are quite different with those of heterogenous concrete block. However, their average force-displacement relationship show a pretty close match each other.

• Atmosphere
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• v.22 no.1
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• pp.1-12
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• 2012

The Atmospheric motion vectors (AMVs) derived using infrared (IR) channel imagery of geostationary satellites have been utilized widely for real-time weather analysis and data assimilation into global numerical prediction model. As the horizontal resolution of sensors on-board satellites gets higher, it becomes possible to identify atmospheric motions induced by convective clouds ($meso-{\beta}$ and $meso-{\gamma}$ scales). The National Institute of Meteorological Research (NIMR) developed the high resolution visible (HRV) AMV algorithm to detect mesoscale atmospheric motions including ageostrophic flows. To retrieve atmospheric motions smaller than $meso-{\beta}$ scale effectively, the target size is reduced and the visible channel imagery of geostationary satellite with 1 km resolution is used. For the accurate AMVs, optimal conditions are decided by investigating sensitivity of algorithm to target selection and correction method of height assignment. The results show that the optimal conditions are target size of 32 km ${\times}$ 32 km, the grid interval as same as target size, and the optimal target selection method. The HRV AMVs derived with these conditions depict more effectively tropical cyclone OMAIS than IR AMVs and the mean speed of HRV AMVs in OMAIS is slightly faster than that of IR AMVs. Optimized mesoscale AMVs are derived for 6 months (Feb. 2010-Jun. 2010) and validated with radiosonde observations, which indicates NIMR's HRV AMV algorithm can retrieve successfully mesoscale atmospheric motions.